An Immunological Approach to Mobile Robot Navigation

Abstract

Autonomous mobile robots have a wide range of applications in industries, hospitals, offices, and even the military, due to their superior mobility. Some of their capabilities include automatic driving, intelligent delivery agents, assistance to the disabled, exploration and map generation for environmental cleanup, etc. In addition, their capabilities also allow them to carry out specialized tasks in environments inaccessible or very hazardous for human beings such as nuclear plants and chemical handling. They are also useful in emergencies for fire extinguishing and rescue operations. Combined with manipulation abilities, their capabilities and efficiency will increase and can be used for dangerous tasks such as security guard, exposition processing, as well as undersea, underground and even space exploration. In order to adapt the robot's behavior to any complex, varying and unknown environment without further human intervention, intelligent mobile robots should be able to extract information from the environment, use their built-in knowledge to perceive, act and adapt within the environment. An autonomous robot must be able to maneuver effectively in its environment, achieving its goals while avoiding collisions with static and moving obstacles. As a result, motion planning for mobile robots plays an important role in robotics and has thus attracted the attention of researchers recently. The design goal for path planning is to enable a mobile robot to navigate safely and efficiently without collisions to a target position in an unknown and complex environment. The navigation strategies of mobile robots can be generally classified into two categories, global path planning and local reactive navigation. The former is done offline and the robot has complete prior knowledge about the shape, location, orientation, and even the movements of the obstacles in the environment. Its path is derived utilizing some optimization techniques to minimize the cost of the search. However, it has difficulty handling a modification of the environment, due to some uncertain environmental situations, and the reactive navigation capabilities are indispensable since the real-world environments are apt to change over time. On the other hand, local reactive navigation employing some reactive strategies to perceive the environment based on the sensory information and path planning is done online. The robot has to acquire a set of stimulus-action mechanisms through its sensory inputs, such as distance information from sonar and laser sensors, visual information from cameras or processed data derived after appropriate fusion of numerous sensor outputs. The action